Biomechanical models that describe soft-tissue deformations provide a relatively inexpensive way to correct registration
errors in image guided neurosurgical systems caused by non-rigid brain shifts. Quantifying the factors that cause this
deformation to sufficient precision is a challenging task. To circumvent this difficulty, atlas-based method have been
developed recently which allow for uncertainty yet still capture the first order effects associated with brain deformations.
More specifically, the technique involves building an atlas of solutions to account for the statistical uncertainty in factors
that control the direction and magnitude of brain shift. The inverse solution is driven by a sparse intraoperative surface
measurement. Since this subset of data only provides surface information, it could bias the reconstruction and affect the
subsurface accuracy of the model prediction. Studies in intraoperative MR have shown that the deformation in the
midline, tentorium, and contralateral hemisphere is relatively small. The falx cerebri and tentorium cerebelli, two of the
important dural septa, act as rigid membranes supporting the brain parenchyma and compartmentalizing the brain.
Accounting for these structures in models may be an important key to improving subsurface shift accuracy. The goals of
this paper are to describe a novel method developed to segment the tentorium cerebelli, develop the procedure for
modeling the dural septa and study the effect of those membranes on subsurface brain shift.
A patient specific finite element biphasic brain model has been utilized to codify a surgeon's experience by establishing
quantifiable biomechanical measures to score orientations for optimal planning of brain tumor resection. When faced
with evaluating several potential approaches to tumor removal during preoperative planning, the goal of this work is to
facilitate the surgeon's selection of a patient head orientation such that tumor presentation and resection is assisted via
favorable brain shift conditions rather than trying to allay confounding ones. Displacement-based measures consisting of
area classification of the brain surface shifting in the craniotomy region and lateral displacement of the tumor center
relative to an approach vector defined by the surgeon were calculated over a range of orientations and used to form an
objective function. The objective function was used in conjunction with Levenberg-Marquardt optimization to find the
ideal patient orientation. For a frontal lobe tumor presentation the model predicts an ideal orientation that indicates the
patient should be placed in a lateral decubitus position on the side contralateral to the tumor in order to minimize
unfavorable brain shift.